Merge pull request #154 from mrava87/master

Added changelog for v1.9.1

Author: mrava87

CHANGELOG.md

@@ -1,3 +1,15 @@
+# 1.9.1
+* Changed internal behaviour of ``pylops.sparsity.OMP`` when
+  `niter_inner=0`. Automatically reverts to Matching Pursuit algorithm.
+* Changed handling of `dtype` in ``pylops.signalprocessing.FFT`` and
+  ``pylops.signalprocessing.FFT2D`` to ensure that the type of the input
+  vector is retained when applying forward and adjoint.
+* Added `dtype` parameter to the `FFT` calls in the definition of the
+  ``pylops.waveeqprocessing.MDD`` operation. This ensure that the type
+  of the real part of `G` input is enforced to the output vectors of the
+  forward and adjoint operations.
+
+
 # 1.9.0
 * Added ``pylops.waveeqprocessing.Deghosting`` and
   ``pylops.signalprocessing.Seislet`` operators

docs/source/changelog.rst

@@ -3,6 +3,26 @@
 Changelog
 =========
 
+
+Version 1.9.1
+-------------
+
+*Released on: 25/05/2020*
+
+* Changed internal behaviour of :func:`pylops.sparsity.OMP` when
+  ``niter_inner=0``. Automatically reverts to Matching Pursuit algorithm.
+
+* Changed handling of ``dtype`` in :class:`pylops.signalprocessing.FFT` and
+  :class:`pylops.signalprocessing.FFT2D` to ensure that the type of the input
+  vector is retained when applying forward and adjoint.
+
+* Added ``dtype`` parameter to the ``FFT`` calls in the definition of the
+  :class:`pylops.waveeqprocessing.MDD` operation. This ensure that the type
+  of the real part of ``G`` input is enforced to the output vectors of the
+  forward and adjoint operations.
+
+
+
 Version 1.9.0
 -------------
 

pylops/optimization/sparsity.py

@@ -1138,7 +1138,7 @@ def SplitBregman(Op, RegsL1, data, niter_outer=3, niter_inner=5, RegsL2=None,
         J = \mu/2 ||\textbf{d} - \textbf{Op} \textbf{x} |||_2 +
         \sum_i \epsilon_{{R}_{L2,i}} ||\mathbf{d_{{R}_{L2,i}}} -
         \mathbf{R_{L2,i}} \textbf{x} |||_2 +
-        \sum_i || \mathbf{R_{L1,i}} \textbf{x} |||_1
+        \sum_i \epsilon_{{R}_{L1,i}} || \mathbf{R_{L1,i}} \textbf{x} |||_1
 
     where :math:`\mu` and :math:`\epsilon_{{R}_{L2,i}}` are the damping factors
     used to weight the different terms of the cost function.